






"""simple docstring"""





import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_SCREAMING_SNAKE_CASE   :							Dict          =		get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
@require_tokenizers
class 	a		(   __snake_case    , unittest.TestCase						):
    SCREAMING_SNAKE_CASE		:	Dict		=					XLMRobertaTokenizer
    SCREAMING_SNAKE_CASE		:	List[str]		=					XLMRobertaTokenizerFast
    SCREAMING_SNAKE_CASE		:	str		=					True
    SCREAMING_SNAKE_CASE		:	int		=					True






    def   UpperCamelCase			(			self	:				List[str]   )	->						Optional[Any]:
      super().setUp()

      # We have a SentencePiece fixture for testing
      lowerCamelCase_       	=		XLMRobertaTokenizer(__SCREAMING_SNAKE_CASE			,		keep_accents=__SCREAMING_SNAKE_CASE   )
      tokenizer.save_pretrained(self.tmpdirname   )






    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						Dict:
      lowerCamelCase_       	=		'<pad>'
      lowerCamelCase_       	=		1

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				List[str]   )	->						List[Any]:
      lowerCamelCase_       	=		list(self.get_tokenizer().get_vocab().keys()   )

      self.assertEqual(vocab_keys[0]			,		'<s>'   )
      self.assertEqual(vocab_keys[1]			,		'<pad>'   )
      self.assertEqual(vocab_keys[-1]			,		'<mask>'   )
      self.assertEqual(len(__SCREAMING_SNAKE_CASE   )			,		1002   )






    def   UpperCamelCase			(			self	:				str   )	->						str:
      self.assertEqual(self.get_tokenizer().vocab_size			,		1002   )






    def   UpperCamelCase			(			self	:				Tuple   )	->						str:
      lowerCamelCase_       	=		XLMRobertaTokenizer(__SCREAMING_SNAKE_CASE			,		keep_accents=__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		tokenizer.tokenize('This is a test'   )
      self.assertListEqual(__SCREAMING_SNAKE_CASE			,		['▁This', '▁is', '▁a', '▁t', 'est']   )

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE   )			,		[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			,		)

      lowerCamelCase_       	=		tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
      self.assertListEqual(
          __SCREAMING_SNAKE_CASE			,		[
              SPIECE_UNDERLINE + 'I',
              SPIECE_UNDERLINE + 'was',
              SPIECE_UNDERLINE + 'b',
              'or',
              'n',
              SPIECE_UNDERLINE + 'in',
              SPIECE_UNDERLINE + '',
              '9',
              '2',
              '0',
              '0',
              '0',
              ',',
              SPIECE_UNDERLINE + 'and',
              SPIECE_UNDERLINE + 'this',
              SPIECE_UNDERLINE + 'is',
              SPIECE_UNDERLINE + 'f',
              'al',
              's',
              'é',
              '.',
          ]			,		)
      lowerCamelCase_       	=		tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE   )
      self.assertListEqual(
          __SCREAMING_SNAKE_CASE			,		[
              value + tokenizer.fairseq_offset
              for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
              #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
          ]			,		)

      lowerCamelCase_       	=		tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE   )
      self.assertListEqual(
          __SCREAMING_SNAKE_CASE			,		[
              SPIECE_UNDERLINE + 'I',
              SPIECE_UNDERLINE + 'was',
              SPIECE_UNDERLINE + 'b',
              'or',
              'n',
              SPIECE_UNDERLINE + 'in',
              SPIECE_UNDERLINE + '',
              '<unk>',
              '2',
              '0',
              '0',
              '0',
              ',',
              SPIECE_UNDERLINE + 'and',
              SPIECE_UNDERLINE + 'this',
              SPIECE_UNDERLINE + 'is',
              SPIECE_UNDERLINE + 'f',
              'al',
              's',
              '<unk>',
              '.',
          ]			,		)






    def   UpperCamelCase			(			self	:				int   )	->						str:
      if not self.test_slow_tokenizer:
        # as we don't have a slow version, we can't compare the outputs between slow and fast versions
        return

      lowerCamelCase_       	=		(self.rust_tokenizer_class, 'hf-internal-testing/tiny-xlm-roberta', {})
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
          lowerCamelCase_       	=		self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE			,		**__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		self.tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE			,		**__SCREAMING_SNAKE_CASE   )

          lowerCamelCase_       	=		tempfile.mkdtemp()

          lowerCamelCase_       	=		tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		tokenizer_p.save_pretrained(__SCREAMING_SNAKE_CASE   )

          # Checks it save with the same files + the tokenizer.json file for the fast one
          self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files   )   )
          lowerCamelCase_       	=		tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f   )
          self.assertSequenceEqual(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

          # Checks everything loads correctly in the same way
          lowerCamelCase_       	=		tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE   )

          # Check special tokens are set accordingly on Rust and Python
          for key in tokenizer_pp.special_tokens_map:
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )   )
            # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
            # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

          shutil.rmtree(__SCREAMING_SNAKE_CASE   )

          # Save tokenizer rust, legacy_format=True
          lowerCamelCase_       	=		tempfile.mkdtemp()

          lowerCamelCase_       	=		tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE			,		legacy_format=__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		tokenizer_p.save_pretrained(__SCREAMING_SNAKE_CASE   )

          # Checks it save with the same files
          self.assertSequenceEqual(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

          # Checks everything loads correctly in the same way
          lowerCamelCase_       	=		tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE   )

          # Check special tokens are set accordingly on Rust and Python
          for key in tokenizer_pp.special_tokens_map:
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )   )

          shutil.rmtree(__SCREAMING_SNAKE_CASE   )

          # Save tokenizer rust, legacy_format=False
          lowerCamelCase_       	=		tempfile.mkdtemp()

          lowerCamelCase_       	=		tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE			,		legacy_format=__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		tokenizer_p.save_pretrained(__SCREAMING_SNAKE_CASE   )

          # Checks it saved the tokenizer.json file
          self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files   )   )

          # Checks everything loads correctly in the same way
          lowerCamelCase_       	=		tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE   )

          # Check special tokens are set accordingly on Rust and Python
          for key in tokenizer_pp.special_tokens_map:
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )   )

          shutil.rmtree(__SCREAMING_SNAKE_CASE   )






    @cached_property
    def   UpperCamelCase			(			self	:				str   )	->						int:
      return XLMRobertaTokenizer.from_pretrained('xlm-roberta-base'   )






    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						int:
      with tempfile.NamedTemporaryFile() as f:
        shutil.copyfile(__SCREAMING_SNAKE_CASE			,		f.name   )
        lowerCamelCase_       	=		XLMRobertaTokenizer(f.name			,		keep_accents=__SCREAMING_SNAKE_CASE   )
        lowerCamelCase_       	=		pickle.dumps(__SCREAMING_SNAKE_CASE   )
      pickle.loads(__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				Any   )	->						Dict:
      if not self.test_rust_tokenizer:
        return

      lowerCamelCase_       	=		self.get_tokenizer()
      lowerCamelCase_       	=		self.get_rust_tokenizer()

      lowerCamelCase_       	=		'I was born in 92000, and this is falsé.'

      lowerCamelCase_       	=		tokenizer.tokenize(__SCREAMING_SNAKE_CASE   )
      lowerCamelCase_       	=		rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE   )
      self.assertListEqual(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		tokenizer.encode(__SCREAMING_SNAKE_CASE			,		add_special_tokens=__SCREAMING_SNAKE_CASE   )
      lowerCamelCase_       	=		rust_tokenizer.encode(__SCREAMING_SNAKE_CASE			,		add_special_tokens=__SCREAMING_SNAKE_CASE   )
      self.assertListEqual(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		self.get_rust_tokenizer()
      lowerCamelCase_       	=		tokenizer.encode(__SCREAMING_SNAKE_CASE   )
      lowerCamelCase_       	=		rust_tokenizer.encode(__SCREAMING_SNAKE_CASE   )
      self.assertListEqual(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )






    @slow
    def   UpperCamelCase			(			self	:				List[Any]   )	->						str:
      lowerCamelCase_       	=		'Hello World!'
      lowerCamelCase_       	=		[0, 35378, 6661, 38, 2]
      # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
      # xlmr.eval()
      # xlmr.encode(symbols)

      self.assertListEqual(__SCREAMING_SNAKE_CASE			,		self.big_tokenizer.encode(__SCREAMING_SNAKE_CASE   )   )






    @slow
    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						Dict:
      lowerCamelCase_       	=		(
          'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
          ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
      )
      lowerCamelCase_       	=		[
          0,
          3293,
          83,
          10,
          4552,
          4989,
          7986,
          678,
          10,
          5915,
          111,
          179459,
          124850,
          4,
          6044,
          237,
          12,
          6,
          5,
          6,
          4,
          6780,
          705,
          15,
          1388,
          44,
          378,
          10114,
          711,
          152,
          20,
          6,
          5,
          22376,
          642,
          1221,
          15190,
          34153,
          450,
          5608,
          959,
          1119,
          57702,
          136,
          186,
          47,
          1098,
          29367,
          47,
          # 4426, # What fairseq tokenizes from "<unk>": "_<"
          # 3678, # What fairseq tokenizes from "<unk>": "unk"
          # 2740, # What fairseq tokenizes from "<unk>": ">"
          3,  # What we tokenize from "<unk>": "<unk>"
          6,  # Residue from the tokenization: an extra sentencepiece underline
          4,
          6044,
          237,
          6284,
          50901,
          528,
          31,
          90,
          34,
          927,
          2,
      ]
      # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
      # xlmr.eval()
      # xlmr.encode(symbols)

      self.assertListEqual(__SCREAMING_SNAKE_CASE			,		self.big_tokenizer.encode(__SCREAMING_SNAKE_CASE   )   )






    @slow
    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						Union[str, Any]:
      # fmt: off
      lowerCamelCase_       	=		{'input_ids': [[0, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [0, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
      # fmt: on

      self.tokenizer_integration_test_util(
          expected_encoding=__SCREAMING_SNAKE_CASE			,		model_name='xlm-roberta-base'			,		revision='d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'			,		)












"""simple docstring"""





_SCREAMING_SNAKE_CASE   :							Optional[int]          =		8.314_4598







def 	lowerCamelCase__			(				_lowerCamelCase			:						float						,							_lowerCamelCase			:						float					) ->							float:
  if temperature < 0:
    raise Exception('Temperature cannot be less than 0 K'					)
  if molar_mass <= 0:
    raise Exception('Molar mass cannot be less than or equal to 0 kg/mol'					)
  else:
    return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
  import doctest

  # run doctest
  doctest.testmod()

  # example
  _SCREAMING_SNAKE_CASE   :							List[Any]          =		300
  _SCREAMING_SNAKE_CASE   :							Dict          =		28
  _SCREAMING_SNAKE_CASE   :							List[str]          =		rms_speed_of_molecule(temperature, molar_mass)
  print(F'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')




